In the structure of ANFIS, there are two different parameter groups: premise and
consequence. Training ANFIS means determination of these parameters using an …

This paper presents the results of the Adaptive-Network Based Fuzzy Inference System
(ANFIS) for the prediction of path loss in a specific urban environment. A new algorithm …

In many reliability analyses, the probability of obtaining a defective unit in a production
process should not be considered constant even though the process is stable and in control …

Exact guaranteed-coverage and expected-coverage Bayesian tolerance limits for the
lifetime distribution of a k-out-of-n: F system are computed by solving nonlinear equations …

In this paper, the fuzzy regression model is considered with crisp inputs and symmetric
triangular fuzzy output. This study aims to formulate the fuzzy inference system based on the …

In this study, we present an approach based on neural networks, as an alternative to the
ordinary least squares method, to describe the relation between the dependent and …

Popular regression techniques often suffer at the presence of data outliers. The different
methods have proposed to make smaller the effect of the outlier on the parameter estimates …

To address the compounded uncertainty in the observed output data, we introduce a new
method of fuzzy regression modeling which is based on quadratic programming and fuzzy …

Uyarlamalı ağ tabanlı bulanık çıkarım sistemi (ANFIS), son yıllarda yapay zekâ çalışmaları
kapsamında sıklıkla tercih edilen yöntemlerden birisidir. Birçok farklı alanda ve farklı türde …

Fuzzy regression analysis is one of the most widely used statistical techniques which
represents the relation between variables. In this paper, the crisp inputs and the symmetrical …